HPDinterval.mtar: Highest Posterior Density intervals for objects of class...

In mtarm: Bayesian Estimation of Multivariate Threshold Autoregressive Models

Highest Posterior Density intervals for objects of class mtar

Description

Highest Posterior Density intervals for objects of class mtar

Usage

## S3 method for class 'mtar'
HPDinterval(obj, prob = 0.95, ...)

Arguments

obj	an object of class mtar generated by a call to the function mtar().
prob	a numeric scalar in the interval (0,1) giving the target probability content of the intervals. By default, prob is set to 0.95.
...	Optional additional arguments for methods. None are used at present.

See Also

HPDinterval

Examples

###### Example 1: Returns of the closing prices of three financial indexes
data(returns)
fit1 <- mtar(~ COLCAP + BOVESPA | SP500, data=returns, row.names=Date,
             subset={Date<="2015-12-07"}, dist="Student-t",
             ars=ars(nregim=3,p=c(1,1,2)), n.burnin=1000, n.sim=2000,
             n.thin=2, ssvs=TRUE)
coda::HPDinterval(fit1)

###### Example 2: Rainfall and two river flows in Colombia
data(riverflows)
fit2 <- mtar(~ Bedon + LaPlata | Rainfall, data=riverflows, row.names=Date,
             subset={Date<="2009-02-13"}, dist="Laplace",
             ars=ars(nregim=3,p=5), n.burnin=1000, n.sim=2000, n.thin=2)
coda::HPDinterval(fit2)

###### Example 3: Temperature, precipitation, and two river flows in Iceland
data(iceland.rf)
fit3 <- mtar(~ Jokulsa + Vatnsdalsa | Temperature | Precipitation,
             data=iceland.rf, subset={Date<="1974-11-06"}, row.names=Date,
             ars=ars(nregim=2,p=15,q=4,d=2), n.burnin=1000, n.sim=2000,
             n.thin=2, dist="Slash")
coda::HPDinterval(fit3)

###### Example 4: U.S. stock returns
data(US.returns)
fit4 <- mtar(~ CCR | dVIX, data=US.returns, subset={Date<="2025-11-28"},
             row.names=Date, ars=ars(nregim=2,p=3,d=3), n.burnin=1000,
             n.sim=2000, n.thin=2, dist="Student-t")
coda::HPDinterval(fit4)

mtarm documentation built on June 12, 2026, 5:07 p.m.